Can I mix different architectures in a cluster?

Technically yes, but it's not recommended for performance-critical workloads. Different architectures have different capabilities (Tensor Core generations, precision support, NVLink bandwidth) that can create bottlenecks. For distributed training, it's best to use identical GPUs. However, for inference serving or development/testing, mixing architectures is fine.